import os, sys
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
import tensorflow as tf # v2.5.0
from tensorflow import keras

def load_image(f):
  return tf.io.decode_image(tf.io.read_file(f), channels=1, dtype=tf.float32)

with tf.device("/CPU:0"):
  model = tf.keras.models.load_model("model")
  image = tf.expand_dims(load_image(sys.argv[1]), axis=0)
  results = model.predict(image)[0]
  names = ["airplane", "automobile", "bird", "cat", "deer", "dog", "frog", "horse", "ship", "truck", "flag"]
  for name, result in zip(names, results):
    print(f"{name:10} {result*100:6.2f} %")